Biology – Quantitative Biology – Biomolecules
Scientific paper
2006-06-12
Journal of Chemical Theory and Computation, Volume 2 Issue 3 (May 09, 2006)
Biology
Quantitative Biology
Biomolecules
Scientific paper
10.1021/ct0600058
Over the last 10-15 years a general understanding of the chemical reaction of protein folding has emerged from statistical mechanics. The lessons learned from protein folding kinetics based on energy landscape ideas have benefited protein structure prediction, in particular the development of coarse grained models. We survey results from blind structure prediction. We explore how second generation prediction energy functions can be developed by introducing information from an ensemble of previously simulated structures. This procedure relies on the assumption of a funnelled energy landscape keeping with the principle of minimal frustration. First generation simulated structures provide an improved input for associative memory energy functions in comparison to the experimental protein structures chosen on the basis of sequence alignment.
Eastwood Michael P.
Hardin Corey
Prentiss Michael C.
Wolynes Peter G.
Zong Chenghong
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